Using BP Network for Occlusion Boundary Detection Based on Depth Image
ZHANG Shi-hui1,2,GENG Yong1,ZHANG Xiao-wei1
1. School of Information Science and Engineering, Yanshan University, Qinhuangdao, Hebei 066004,China
2. The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province,Qinhuangdao, Hebei 066004,China
Abstract Aiming at the occlusion phenomena existing in visual object, an occlusion boundary detection approach is proposed based on machine learning for depth image. Firstly, a novel occlusion related feature named the longest projected line segment is presented according to the depth and spatial information in depth image. Secondly, a nonlinear normalization method is designed to normalize the occlusion related features. Finally, the problem of occlusion boundary detection is taken as a classification problem, meanwhile, the back propagation(BP) neural network is utilized to detect the occlusion boundary and then the detection result is visualized. Compared with existing methods, the proposed approach is more accurate and the generalization performance is better.
ZHANG Shi-hui,GENG Yong,ZHANG Xiao-wei. Using BP Network for Occlusion Boundary Detection Based on Depth Image[J]. Acta Metrologica Sinica, 2020, 41(10): 1205-1211.
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2020, Vol. 41 
